#!/usr/bin/env python
# coding: utf-8

# ## An initial concentration pulse (near the left edge of the system, and halfway vertically) moving towards equilibrium
# 
# The system starts out with a "concentration pulse" in just one bin - i.e. that bin is initially the only one with a non-zero concentration of the only chemical species.
# Then the system is left undisturbed, and followed to equilibrium.
# 
# (Note: this is the 2D counterpart of the 1D experiment by the same name)
# 
# LAST REVISED: Nov. 28, 2022

# In[1]:


# Extend the sys.path variable, to contain the project's root directory
import set_path
set_path.add_ancestor_dir_to_syspath(3)  # The number of levels to go up 
                                         # to reach the project's home, from the folder containing this notebook


# In[2]:


from experiments.get_notebook_info import get_notebook_basename

from src.life_2D.bio_sim_2d import BioSim2D

import plotly.express as px
import plotly.graph_objects as go

from src.modules.reactions.reaction_data import ReactionData as chem


# In[3]:


# Prepare the initial system, with a single non-zero bin, near the left edge of the system, positioned halfway vertically
chem_data = chem(names=["A"], diffusion_rates=[0.02])
bio = BioSim2D(n_bins=(5, 8), chem_data=chem_data)

bio.inject_conc_to_bin(bin_address=(2, 1), species_index=0, delta_conc=10.)

bio.describe_state()


# In[4]:


bio.system_snapshot()


# In[5]:


fig = px.imshow(bio.system_snapshot(), 
                title= f"Diffusion. System snapshot as a heatmap at time t={bio.system_time}", 
                labels=dict(x="x (col. number)", y="y (row number)", color="Concentration"),
                text_auto=True, color_continuous_scale="gray_r")         # text_auto=’.2f’

fig.data[0].xgap=2
fig.data[0].ygap=2

fig.show()


# # Initial Diffusion Step

# In[6]:


delta_time = 10.

status = bio.diffuse(total_duration=delta_time, time_step=0.1)
print("\n", status)

bio.describe_state()


# In[7]:


fig = px.imshow(bio.system_snapshot(), 
                title= f"Diffusion. System snapshot as a heatmap at time t={bio.system_time}", 
                labels=dict(x="x (col. number)", y="y (row number)", color="Concentration"),
                text_auto='.2f', color_continuous_scale="gray_r")

fig.data[0].xgap=2
fig.data[0].ygap=2

fig.show()


# ## This is still an early stage in the diffusion process; let's advance it more... (Visualization from results shown at selected times)

# In[8]:


for i in range(200):
    status = bio.diffuse(total_duration=delta_time, time_step=0.1)

    if i<2 or i==6 or i>=199:
        bio.describe_state()
        fig = px.imshow(bio.system_snapshot(), 
                title= f"Diffusion. System snapshot as a heatmap at time t={bio.system_time}", 
                labels=dict(x="x (col. number)", y="y (row number)", color="Concentration"),
                text_auto='.2f', color_continuous_scale="gray_r")

        fig.data[0].xgap=2
        fig.data[0].ygap=2

        fig.show()


# ## All bins now have essentially uniform concentration
# 
# Notice the continued symmetry across the mid-row.
# 
# **Mass conservations**: the "10. units of concentration" are now uniformly spread across the 40 bins, leading to a near-constant concentration of 10./40

# In[9]:


10./40


# In[ ]: